Teaching
- Research Methodology (MCC500): Winter 2024
- Operating Systems Lab (MCC512): Winter 2024
- Engineering Mathematics-I (NMCI101): Monsoon 2024
- Engineering Mathematics-II (NMCI101): Winter 2025
- Preparatory Mathematics-I (NMCP101): Monsoon 2024
Designation: Assistant Professor
Department: Mathematics & Computing
Email: ashokdas[at]iitism[dot]ac[dot]in
Contact Number: 9681442503
Office Number: +91-326-223-5437
Personal Page: Click Here
About Me: Dr. Ashok Das is an Assistant Professor at the Department of Mathematics & Computing, IIT (ISM) Dhanbad, India. Prior to joining this current position, he had worked as a post-doc at the Institut Jean Lamour, Université de Lorraine, France and Bernal Institute, University of Limerick, Ireland. He completed his M.Sc. and PhD in Mathematics from IIT Kharagpur in 2016 and 2022, respectively. He has received the B.Sc. degree from Hooghly Mohsin College, University of Burdwan in 2014. During his life, he had received several recognized national level academic scholarships, including IIT Kharagpur Research fellowship, INSPIRE scholarship, Merit-Cum-Means scholarship.
Research Interest: Dr. Ashok Das's research focuses on the modeling, simulation, and analysis of particulate processes. Particulate matter is present across a wide range of industries, from pharmaceuticals to food processing, and spans an extensive size range—from nanoparticles in advanced materials to large-scale astronomical objects—highlighting its universal significance in both natural and industrial processes. As particles undergo various interaction processes, they exhibit critical changes in properties such as size, volume, shape, and temperature. Accurately controlling and predicting these changes is essential for optimizing process outcomes. Dr. Das and his research team employ advanced mathematical and computational techniques, including Population Balance Modeling (PBM), the Discrete Element Method (DEM), and multiscale modeling, to investigate these phenomena. The goal is to develop state-of-the-art mathematical frameworks and simulation software to enhance the prediction and control of both physical and industrial particulate processes.
Ongoing Ph.D Students: